text:
Update 'samples/sample_extension' to Dart 2

Ran dartfmt --fix
Fixed Dart 2 type errors
Other misc cleanup (to conform to Effective Dart)

Contributes to https://github.com/dart-lang/site-www/issues/980
cc @a-siva @kwalrath @kevmoo

Yes! expect is SDK-only
On Fri, Jun 29, 2018 at 9:59 AM Patrice Chalin notifications@github.com
wrote:

@chalin commented on this pull request.
In samples/sample_extension/test/sample_extension_test_helper.dart
https://github.com/dart-lang/sdk/pull/33711#discussion_r199221690:

-import "package:expect/expect.dart";
+import "package:test/test.dart";
I couldn't find an expect package in pub. Could test be used here?
—
You are receiving this because you were mentioned.
Reply to this email directly, view it on GitHub
https://github.com/dart-lang/sdk/pull/33711#pullrequestreview-133303513,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AABCihdd9YUVQ3tFa8M4W4P7knvNfeX7ks5uBlzZgaJpZM4U9VFL
.

@a-siva - Under SDK 2-dev.66, the analyzer reports no issues (even with no implicit casts, and no implicit dynamic). The following tests pass:

dart test_sample_asynchronous_extension.dart
dart test_sample_synchronous_extension.dart

See https://dart-review.googlesource.com/c/sdk/+/63260

Any update on this?

Need to comment here - https://dart-review.googlesource.com/c/sdk/+/63260 – now the source of truth

@chalin @kevmoo what is the status of this PR?

ping...

Just a note, sample_extension/test/sample_extension_test still fails under dartk (see this log for example), so putting that back into the RuntimeError state in the status file for now.

HI Stevie! Thanks for the note. Maybe if it fails intermittently, it would be best to skip that test?

Perhaps! For now, I've at least marked it as possibly doing Pass and RuntimeError, and maybe we can figure out if there's a way to get rid of that latter while still catching any other type of failures in the meantime :)

SGTM

authors: chalin kevmoo kwalrath mit-mit sstrickl


text:
Request: Sankey diagram

A few months ago the ability to create Sankey diagrams was added to Mermaid.  It would change my life if I could create these in Obsidian.
Mermaid: Sankey diagram

@jspronk you can! This plugin does not affect rendering Mermaid at any way, it just provides a convenient toolbar :)
There are some problems with rendering Sankey (it's still beta) in the toolbar, so I won't be adding it to the toolbar until these are fixes.

Oh nice!
Do you happen to have a working example you could share? I'm playing with the syntax and just cant seem to get any diagram to rendder...instead I get the following:
Error parsing Mermaid diagram!

No diagram type detected matching given configuration for text: sankey

This issue is strangely timely: From the beginning of the year through last Friday, Jan 12, 2024, I had been using Obsidian to develop and render mermaid Sanke diagrams to great effect.  Today, I tried to view some of my erstwhile beautiful diagrams but found them to be missing the colorful connection flows!  Even the simple example from the mermaid docs at https://mermaid.js.org/syntax/sankey.html :
sankey-beta
%% source,target,value
Electricity grid,Over generation / exports,104.453
Electricity grid,Heating and cooling - homes,113.726
Electricity grid,H2 conversion,27.14

renders as:

instead of (as it did last week):

I've got no clue what might be wrong and I don't understand what resource chain is used by Obsidian to get the ultimate image.  I can say that it's not a wholesale mermaid issue as all of the Gantt and  Flowcharts that I viewed still look fine.
-Phil

I am having the same issue.

@jspronk @PDWest examples from https://mermaid.js.org/syntax/sankey.html worked fine for me, however right now there is indeed some trouble with Obsidian's rendering of Mermaid... Nothing I can do about that, your best bet is creating bug on official forums :(

source: gharchive/issue

authors: PDWest dartungar jspronk

repo: dartungar/obsidian-mermaid

license: MIT

license_type: permissive

license_source: github-api


text:
Added the img directory to the main section of bower.json so that gul…

Added the img directory to the "main" section of bower.json so that gulp's main-bower-files task will run correctly. main-bower-files uses the entries in the "main" section to create its list of source files to pipe to the next gulp task. All other files are ignored.

Thx, nice I am not there this week end but put release next week.

source: gharchive/pull-request

license: mit

license_source: bigquery


text:
allow non map step results

resolves #52

Pull Request Test Coverage Report for Build 35ffb2fa87fbf345446449c2e5d116f989422c8a-PR-54

9 of 10 (90.0%)  changed or added relevant lines in 1 file are covered.
1 unchanged line in 1 file lost coverage.
Overall coverage increased (+1.1%) to 30.484%

Changes Missing Coverage
Covered Lines
Changed/Added Lines
%

lib/inngest/function/handler.ex
9
10
90.0%

Files with Coverage Reduction
New Missed Lines
%

lib/inngest/function/handler.ex
1
63.64%

Totals

Change from base Build 4ba9741201d081ffe287ddda4f1d9d0292130f89:
1.1%

Covered Lines:
107

Relevant Lines:
351

💛  - Coveralls


text:
New GUI can be drawn in terminal in case of terminal resizing

Listen for CMD +  & CMD - and resize the app (stop the old app and redraw the form again). One more thing can be checked is horizontal vs vertical scaling. How it can fit in ?
Case 1 - Font resizing
Font changing in terminal(before & after rendering)
Scrolling can be an option ?
Tested with drawille, yes the terminal size changes with CMD+ and CMD- not only the font size is increased.
Case 2 - Terminal window resizing
This can be handled easily by checking change in terminal window sizing and then redrawing the GUI.
Solution => Keep listening for the size of the terminal and re-draw.
This will be also helpful
https://groups.google.com/forum/#!msg/npyscreen/anab-NQC_IY/8J4HeQJ-XCQJ;context-place=forum/npyscreen & resizing logic at http://npyscreen.readthedocs.io/form-objects.html

For both the cases now resizing is working but there are two limits that I am observing upper_limit and lower_limit of terminal sizes for which the re-sizing is not working. Need to fix that.

repo: darxtrix/ptop


text:
Container alias resolution

If an explicit container alias points to another explicit alias, it is not resolved from the container (only explicit services are checked and recursively resolved).
Either remove aliases altogether or allow these to be resolved recursively also.

Resolved by the above commit.

repo: darya/framework


text:
docs(metadata-service): refine data model

resolves BS-41
Refine data model, create a json schema and UML diagram

@BalduinLandolt here are my answers to the questions in the datamodel.md and also some comments (in no particular order):
As a general remark, I like to model everything as loosely coupled as possible. There are only two types of values, either value objects or instances of classes. If it has more than one property or it has a chance to be extended in the future, then it is a class.

Class: Grant: is missing id and type. I see grant as a separate thing.

@subotic @mpro7 not much has changed since last review. But I think it's finalized now.

authors: BalduinLandolt subotic

repo: dasch-swiss/dasch-service-platform


text:
Absorb code from 4_solving_schrodingers_equation_in_python

Take code from the notebook and have available for use on the project.

Issue is completed, ready to merge with main.

Yup!

Actually, no.
Forgot to add a way to display the video/image

Ah, i see its up now, merging with main.


text:
feat: include sentinel image version in config

This PR adds the Sentinel image version to config.
Issue being fixed or feature implemented
Sentinel is the only service not yet included and versioned in config. It should be in config so it can be updated independently to mn-bootstrap updates by users directly using mn config:set
What was done?
Added core.sentinel.docker.image setting and upgrade rules.
How Has This Been Tested?
I was unable to test upgrade rules since I'm still not sure how semver parses -dev suffixes, see discussion here.
Breaking Changes

Checklist:

[x] I have performed a self-review of my own code
[x] I have commented my code, particularly in hard-to-understand areas
[x] I have added or updated relevant unit/integration/functional/e2e tests
[x] I have made corresponding changes to the documentation

For repository code-owners and collaborators only

[x] I have assigned this pull request to a milestone

@strophy please resolve conflicts.

authors: shumkov strophy

repo: dashevo/mn-bootstrap


text:
src: Throw proper expections instead of just a string

Based on #4

Should this be done upstream?

Does upstream still maintain V1?

Did this change in v2?

see https://github.com/Chia-Network/bls-signatures/blob/master/src/bls.cpp
These changes can be applied there

Ok yeah partially it could be applied it seems but not for the dash only stuff. And for where it can be applied it doesn't matter that much because its only init means only called once on startup.

I'd like a PR to be opened upstream (doesn't need to be merged upstream) before we merge this PR

See https://github.com/Chia-Network/bls-signatures/pull/147

authors: PastaPastaPasta xdustinface

repo: dashpay/bls-signatures


text:
docs(rpc): remaining v21.0.0 rpc updates

Preview build: https://dash-docs--109.org.readthedocs.build/projects/core/en/109/

Do these "v21.0.0" docs updates include the changes for "v21.1.0" (if any)?
If we don't have docs updates on minor or patch versions would it be better to call them "v21" instead?

This PR doesn't include 21.1 changes, although I don't believe see are any related to RPCs (https://github.com/dashpay/dash/compare/v21.0.0...dashpay:v21.1.0).
As for the branch name, readthedocs (which builds/hosts the content) expects a semver "x.y.z" format for automatically recognizing what to direct people to as the default docs. For example, when you go to docs.dash.org it directs you to https://docs.dash.org/en/stable/ which is the same as if you chose 21.0.0 from the version selector. So v21 might be better, but there are some constraints in play :slightly_smiling_face:
.

Yeah, I've seen the selector on the website, which is why I'm asking follow up questions. It seems to only show major versions like v19.0.0, v20.0.0, etc, so it makes me wonder if v20.0.0 docs are really for the latest v20 docs or literally for v20.0.0. Is there (or will there be) any difference between "latest", v21.0.0, and v21.1.0 (if there will eventually be a separate docs page for that).
If you can change the text to v19, v20, etc

Since Core is now following semver pretty closely, expect to typically just see 21.0.0, 22.0.0, etc. Minor/patch releases should not be making changes significant enough to require a new version of docs. So when you see "X.0.0", assume they're good for all of "vX". In the future if there were a minor/patch version of docs it would likely be due to a deviation in Core's semver that significantly changed something. I don't anticipate Pasta doing that though :slightly_smiling_face:
Regarding the dropdown text... Based on a cursory look, readthedocs directly uses the branch/tag name as the text in the dropdown. I didn't see an option for customizing it.

authors: riongull thephez

repo: dashpay/docs-core


text:
RLS: 0.9.0

Some extra TODOs now that we're using numba

[x] Update setup.cfg to build universal wheels
[x] Update dependencies on conda-forge recipe

This was done.

repo: dask/dask-ml


text:
Multinomial random generator

dask/array/random.py is missing a multinomial random generator (there is aplaceholder # multinomial).
Will dask have a multinomial random generator at some point? Does it require a significantly different approach than the other generators?

See https://github.com/dask/dask/pull/1150

Thanks I appreciate it.
I'll give it a try.

authors: mrocklin yoavram

repo: dask/dask


text:
dask.array.linalg.tsqr incorrectly reported shapes

a = np.random.random((3, 5))
data = da.from_array(a, chunks=5)
q, r = da.linalg.tsqr(data)
q.shape, r.shape

we get...
((3, 5), (5, 5))

wherein the shape of q is wrong. It should be a (3, 3).
But q.compute() correctly yields a 3x3 matrix but of course q.T.dot(q).shape will yield (5,5) which will cause tests to fail (if such tests were there).
I'm presently mucking around tsqr. So perhaps I might tidy up the tests there.

Fix in: https://github.com/dask/dask/pull/3575

cc @jakirkham
On Fri, Jun 8, 2018 at 11:15 PM, Jeremy Chen notifications@github.com
wrote:

a = np.random.random((3, 5))
data = da.from_array(a, chunks=5)
q, r = da.linalg.tsqr(data)
q.shape, r.shape
we get...
((3, 5), (5, 5))
wherein the shape of q is wrong. It should be a (3, 3).
But q.compute() correctly yields a 3x3 matrix but of course
q.T.dot(q).shape will yield (5,5) which will cause tests to fail (if such
tests were there).
I'm presently mucking around tsqr. So perhaps I might tidy up the tests
there.
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/dask/dask/issues/3583, or mute the thread
https://github.com/notifications/unsubscribe-auth/AASszL72X0h4kP9g9GagzisNVpOvQ1yqks5t6z3RgaJpZM4UhJ08
.

authors: convexset mrocklin


text:
Performance issue on compute with reshaped arrays

I ran into a performance issue with related to reshaped dask arrays while using xarray (https://github.com/pydata/xarray/issues/2241). I opened an issue there, but I think this is actually more of a dask issue. Here is some example code which demonstrates the slow down
>>> a = da.random.random((64, 64, 64), (8,8,-1))
>>> b = a.reshape((64**2, 64))
>>> %timeit b[0].compute()
3.2 ms ± 13 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)
>>> %timeit a[0,0].compute()
628 µs ± 13.8 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

b[0] and a[0,0] should in principle refer to the same data, but the reshaped values take almost 4 times as long to compute.
Edit:
This is on dask 0.17.1

I recommend looking at
b[0].visualize('mypicture.png', optimize_graph=True)

You'll find that to produce the first chunk Dask now needs to create and
collect many other chunks, leading to an increased compute time.
On Thu, Jun 21, 2018 at 3:24 AM, Noah D Brenowitz notifications@github.com
wrote:

I ran into a performance issue with related to reshaped dask arrays while
using xarray (pydata/xarray#2241
https://github.com/pydata/xarray/issues/2241). I opened an issue there,
but I think this is actually more of a dask issue. Here is some example
code which demonstrates the slow down

a = da.random.random((64, 64, 64), (8,8,-1))>>> b = a.reshape((64**2, 64))>>> %timeit b[0].compute()3.2 ms ± 13 µs per loop (mean ± std. dev. of 7 runs, 100 loops each)>>> %timeit a[0,0].compute()628 µs ± 13.8 µs per loop (mean ± std. dev. of 7 runs, 1000 loops each)

b[0] and a[0,0] should in principle refer to the same data, but the
reshaped values take almost 4 times as long to compute.
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/dask/dask/issues/3650, or mute the thread
https://github.com/notifications/unsubscribe-auth/AASszAWVVCWWSrNRj553B9Hsq7rind6kks5t-0o7gaJpZM4Uxh52
.

Ok. thanks for tips. I am surprised that dask needs to do all that work since the first chunk of b is just a reshaped version of the first chunk of a.

Note the chunksizes of this arrays:
>>> a
dask.array<random_sample, shape=(64, 64, 64), dtype=float64, chunksize=(8, 8, 64)>
>>> b
dask.array<reshape, shape=(4096, 64), dtype=float64, chunksize=(64, 64)>

When you reshape the first dimensions from (64, 64) to (64**2,), your chunks actually get scrambled: the first 64 elements of b (in its first chunk) read off the first row of the a, which includes 8 different chunks.
When computations are involved, dask doesn't have any way of telling the original da.random.random() that you're indexing out part of the result and it doesn't need to compute full chunks. So considerably more work is done.

your chunks actually get scrambled

Thanks for pointing that out. Now it makes sense to me. I guess the the problem is that the chunks have to be contiguous in the new shape. In principal, I guess strided chunks would fix this performance issue, but I would never expect for such a thing to be implemented in dask. Maybe this issue could be best addressed in xarray by using some smart indexing tricks.
@mrocklin Feel free to close this issue if you want.

Haven't given this a lot of thought. So this suggestion might not work, but have you explored doing rechunking first? If you expand the "fast axes" to the length of the shape first, things might be a bit better. Again haven't test this, but would be curious to hear what you learn from this experiment.

I know it's been a long time since this topic, but I recently ran into unexpected reshape behavior while using dask.delayed or dask-image to load a folder of tiffs and then trying to reshape that folder to reflect the dimensions in the underlying dataset.  For instance:
from dask_image.imread import imread
stack = imread('/data/*.tif')
stack.reshape(600, 2, 64, 256, 280)[0, 0].compute()  # triggers 2 file read events
# this is what I actually need to do to separate dims
stack.reshape(2, 600, 64, 256, 280)[0, 0].compute()  # triggers 600 file read events

As @mrocklin pointed out, using .visualize() is useful to see why...  here's a minimal example with reduced array size:
from dask import delayed
import dask.array as da

@delayed
def f(a,b):
    # simulating a file-read event
    return np.zeros((10, 10))

arr = da.stack(
    [
        da.from_delayed(f(a, b), shape=(10, 10), dtype="float64")
        for a in range(10)
        for b in range(2)
    ]
)
arr.shape  # (20, 10, 10)

arr.reshape(10, 2, 10, 10)[0, 0].visualize()  # 2 calls to f()

arr.reshape(2, 10, 10, 10)[0, 0].visualize()  # 10 calls to f()

I thought rechunking might help... but it doesn't:
rechunked = arr.reshape(2, 10, 10, 10).rechunk((1, 1, 10, 10))
rechunked
# dask.array<rechunk-merge, shape=(2, 10, 10, 10), dtype=float64, chunksize=(1, 1, 10, 10)>

rechunked[0, 0].compute()  # still calls f() 10 times with or without optimize_graph=True

The only way I can think of to avoid this to avoid reshape altogether by manually constructing dask arrays for each dimension, and then stacking them.  As an example for my dask-image use case:
from dask_image.imread import imread
stack = da.stack([imread(f"data/*ch{i}*.tif") for i in range(nchannels)])
# then calling stack[0,0].compute() only incurs one read

that seems a (tiny) bit harder to scale... so just wanted to make sure that's the recommended approach?  thanks!

@shoyer I don't understand why chunks are getting "consolidated" in @tlambert03's example:
In [4]: arr.chunks
Out[4]: ((1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1, 1), (10,), (10,))

In [5]: arr.reshape(2, 10, 10, 10).chunks
Out[5]: ((1, 1), (10,), (10,), (10,))

The chunksize goes from (1, 10, 10) to (1, 10, 10, 10), so stacking of the chunks is happening automatically and, in this case, with a detrimental effect on performance. Unless I'm misunderstanding what's happening, it seems to me that reshape and other functions should gain the ability to turn off automatic rechunking, and this problem would then go away?

Yeah, I don’t understand what is going on in that example. It looks like a bit of a different situation than what is described in the original issue here.

The rehsape algorithm is setup to rechunk into singleton chunks along all but the first dimension.
I created an example PR to show a shortcut when collapsing chunksize=1 reshaping:
https://github.com/deisseroth-lab/dask/commit/39d56b91a016edbcbf01b281da2ba433915ee23a
There has been discussion on this topic here, too
https://github.com/dask/dask/issues/5544
I think getting this optimal in the general case is tricky, but perhaps someone has a slick algorithm.

the explosion of chunks was fixed in #11273

authors: chrisroat jakirkham jni mrocklin nbren12 phofl shoyer tlambert03


text:
dask dataframe - collect list example

Good discussion here about how to implement collect list with dask dataframe https://github.com/dask/dask/issues/2706
I would like to create an example in here: https://docs.dask.org/en/latest/dataframe-groupby.html#aggregate (https://github.com/dask/dask/blob/master/docs/source/dataframe-groupby.rst#aggregate)

That sounds great, thanks!

authors: TomAugspurger raybellwaves


text:
bug report svd_compressed() fails at calculating svd for complex matrix

What happened:
svd_compressed() fails at calculating svd for complex matrix. I reconstructed the matrix using M'=UΣV^† . The real matrix input yields reasonable answer, and it fails for complex matrix input.
I calculated the trace and norm of M-M' (M:original matrix; M':M'~UΣV^†) which should be small. On the complex case, difference between M and M' is large.
trace:(768972.9893344672+7563949.776901031j)
norm:54801713.60352144

But on the real case, it yields a reasonable answer.
trace:-2.470109161656353e-08
norm:1.8832952585877038e-07

What you expected to happen:
On the case of complex matrix input, the trace and norm of M-M' should be small.
Here is my code:

code:
import os
import sys
import time
import numpy as np
from opt_einsum import contract

from dask.distributed import Client
from dask_cuda import LocalCUDACluster
from dask_cuda.initialize import initialize
from dask.utils import parse_bytes
from dask.distributed import performance_report
from dask.distributed import wait
from dask.distributed import get_task_stream

import cupy
import rmm
import cudf
import dask.array as da

def setup_rmm_pool(client):
    client.run(
        cudf.set_allocator,
        pool=False,
        #initial_pool_size= parse_bytes("1GB"),
        allocator="default"
    )
    client.run(
        cupy.cuda.set_allocator,
        #rmm.rmm_cupy_allocator,
        rmm.mr.set_current_device_resource(rmm.mr.ManagedMemoryResource())
    )

if __name__ == "__main__":

    initialize(create_cuda_context=True)

    cluster = LocalCUDACluster(local_directory="./tmp/",
                                memory_limit=None)

    client = Client(cluster)
    setup_rmm_pool(client)

    nprs = np.random.RandomState(seed=1234)
    rs = da.random.RandomState(seed=1234,RandomState=cupy.random.RandomState)

    SIZE = 15000
    k = 32

    b = nprs.rand(SIZE) + 1j * nprs.rand(SIZE)
    b = da.from_array(b, chunks=(5000))
    b = b.map_blocks(cupy.asarray)
    #a = contract("i,j->ij",b,b) * 10
    a = da.einsum("i,j->ij",b,b) * 10
    #a = a.persist()

    a = da.exp(1.2*a)

    t0=time.time()
    u,s,vh=da.linalg.svd_compressed(a,k=k, seed=rs)
    u,s,vh=da.compute(u,s,vh)
    t1=time.time()
    u=da.from_array(u,chunks=(5000,k))
    vh=da.from_array(vh,chunks=(k,5000))

    #b = contract("ij,j,jk->ik",u,s,vh)
    b = da.einsum("ij,j,jk->ik",u,s,vh)
    a = a - b #<-a:M, b:M'
    tr = da.sum(da.diagonal(a)).compute()
    print("trace:{:}".format(tr))
    norm=da.linalg.norm(a).compute()
    print("norm:{:}".format(norm))

    sys.exit(0)

Anything else we need to know?:
Warning occurs while calculating svd:
rapids-22.06/lib/python3.9/site-packages/dask/array/utils.py:101: ComplexWarning: Casting complex values to real discards the imaginary part
  meta = meta.astype(dtype)

And I tried to add
print("meta_from_array:dtype",dtype)

in the "meta_from_array" funtion, and got several "float64", maybe there are some bugs while passing dtype?
Environment:

Dask version: 22.06
Python version: 3.9
Operating System: Linux(HPC)
Install method (conda, pip, source): miniconda

Cluster Dump State:

apologize for forgetting to add a label.


text:
Remove conda-forge from default install instructions

Apparently people were confused by this, and thought that Dask was only
maintained on the conda-forge channel.  We change installation
instructions to explicitly state that Dask is available on either
defaults or conda-forge.  This removes the -c conda-forge flag from
the conda install line.

Any objections to this?


text:
0.5.1 Using s3fs with multiprocessing and pandas.read_csv hangs under certain conditions

I have many csv files that are stored in s3 that I use as part of a pytorch pipeline. As part of the pipeline, I iterate through each of the files using pandas' read_csv function to fit some preprocessing transformers, and then I later use a custom Pytorch dataset/dataloader to feed data to the model itself. This process worked fine until a few weeks ago, when I found that the process of iterating through the data loader would hang immediately if the following was true:

s3fs version >= 0.5.0 (0.4.2 and below works)
I used 2 or more workers in the data loader (0 or 1 worker works even for 0.5.0)
I had already iterated through the files using s3fs/pandas during the preprocessing step (works if I skip the preprocessing iteration and go straight to the data loader)

I further tried to determine if the issue was related to pandas, pytorch, or s3fs. I found that my version of s3fs had switched at some point from 0.4.2 to 0.5.1, which seems to be causing the issue: reverting to 0.4.2 makes everything work again. Additionally process works normally when executing on csv files held locally, when pandas isn't using s3fs to read in the files.
I also looked into possibilities of shared memory problems, the size of the csv files, and the number of files, none of which seemed to be influencing the behavior.
What you expected to happen:
The following works for s3fs 0.4.2 for all values of NUM_WORKERS. Under 0.5.0 and above, if NUM_WORKERS >= 2, and the preprocessing block is run, it hangs immediately for the pytorch dataloader block. It also works if the csv filepaths point to the local machine, and therefore s3fs is not used. For the sake of clarity and conciseness, I've stripped out the actual preprocessing and simply loop through the files.
Minimal Complete Verifiable Example:
import pandas as pd
import torch
from torch.utils.data import IterableDataset, ChainDataset, DataLoader

# Pytorch csv iterable dataset
class CsvDataset(IterableDataset):
    def __init__(self, filename):
        self.filename = filename

    def __iter__(self):
        data = pd.read_csv(self.filename).values.tolist()
        for line in data:
            yield line

# Iterable dataset for multiple csv files
class MultiCsvDataset(IterableDataset):
    def __init__(self, file_list):
        self.file_list = file_list

    def __iter__(self):
        # Logic for dividing files between multiple workers
        file_list = self.file_list
        worker = torch.utils.data.get_worker_info()
        worker_id = worker.id if worker is not None else -1
        n_workers = worker.num_workers if worker is not None else 0
        if worker:
            file_list = file_list[worker_id::n_workers]

        # Dataset that iterates through chained csv files
        datasets = [CsvDataset(key) for key in file_list]
        dataset = ChainDataset(datasets)

        for line in dataset:
            yield line

KEYS = ["s3://my-bucket/file1.csv", "s3://my-bucket/file2.csv"]
NUM_WORKERS = 2  # Works if 0 or 1, hangs if >= 2
RUN_PREPROCESSING_BLOCK = True

# Preprocessing block (runs, but causes the next block to hang. If skipped, the next block runs fine)
if RUN_PREPROCESSING_BLOCK:
    i = 1
    for key in KEYS:
        pd.read_csv(key)
        print(f"File {i} successful")
        i += 1

# Pytorch dataloader block (works if preprocessing block has not been run, or if NUM_WORKERS < 2,
# or if s3fs version is <= 0.4.2, otherwise hangs indefinitely on the first batch)
dataset = MultiCsvDataset(KEYS)
loader = DataLoader(dataset, batch_size=10, num_workers=NUM_WORKERS)
i = 1
for batch in loader:
    print(f"Batch {i} successful")
    i += 1

Anything else we need to know?:
Environment:

s3fs version: 0.5.1
Python version: 3.7.7
Operating System: MacOS, also Linux Docker container
Install method (conda, pip, source): pip

Thanks for the report.
Do you know if multiprocessing works by fork (i.e., you get a copy of the memory in the child processes) or spawn (i.e., you get a new process, and objects are sent by pickle)? Could you try with the other method for starting processes? See https://docs.python.org/3/library/multiprocessing.html#contexts-and-start-methods It seems to me that spawn and forkserver work OK, but fork (default on linux) does not.

Pytorch dataloader block (works if preprocessing block has not been run

Would you mind running s3.clear_instance_cache() in the main process, or instantiate with S3FileSystem(..., skip_instance_cache=True) in the child processes?

PS: thanks for the clear report and investigation.

I am contemplating the following check (which would still not work when attempting to reuse the same s3 instance)
--- a/fsspec/spec.py
+++ b/fsspec/spec.py
@@ -39,6 +39,7 @@ class _Cached(type):
         # collecting instances when all other references are gone. To really
         # delete a FileSystem, the cache must be cleared.
         cls._cache = {}
+        cls._pid = os.getpid()

     def __call__(cls, *args, **kwargs):
         extra_tokens = tuple(
@@ -46,6 +47,9 @@ class _Cached(type):
         )
         token = tokenize(cls, *args, *extra_tokens, **kwargs)
         skip = kwargs.pop("skip_instance_cache", False)
+        if os.getpid() != cls._pid:
+            cls._cache.clear()
+            cls._pid = os.getpid()
         if not skip and cls.cachable and token in cls._cache:
             return cls._cache[token]

Indeed, the default behavior for the data loader is fork (at least on the unix machines I've been using). Switching the method to spawn results in the process running correctly with no hangs. (Note that it appears that trying to change the start method default behavior outside of a "__name__ "== "__main__" block causes problems).
import pandas as pd
import torch
from torch.utils.data import IterableDataset, ChainDataset, DataLoader

# Pytorch csv iterable dataset
class CsvDataset(IterableDataset):
    def __init__(self, filename):
        self.filename = filename

    def __iter__(self):
        data = pd.read_csv(self.filename).values.tolist()
        for line in data:
            yield line

# Iterable dataset for multiple csv files
class MultiCsvDataset(IterableDataset):
    def __init__(self, file_list):
        self.file_list = file_list

    def __iter__(self):
        # Logic for dividing files between multiple workers
        file_list = self.file_list
        worker = torch.utils.data.get_worker_info()
        worker_id = worker.id if worker is not None else -1
        n_workers = worker.num_workers if worker is not None else 0
        if worker:
            file_list = file_list[worker_id::n_workers]

        # Dataset that iterates through chained csv files
        datasets = [CsvDataset(key) for key in file_list]
        dataset = ChainDataset(datasets)

        for line in dataset:
            yield line

if __name__ == "__main__":
    torch.multiprocessing.set_start_method("spawn") # Works if 'spawn', 'fork fails
    KEYS = ["s3://my-bucket/file1.csv", "s3://my-bucket/file2.csv"]
    NUM_WORKERS = 2  # Works if 0 or 1, hangs if >= 2
    RUN_PREPROCESSING_BLOCK = True

    # Preprocessing block (works in all cases)
    if RUN_PREPROCESSING_BLOCK:
        i = 1
        for key in KEYS:
            pd.read_csv(key)
            print(f"File {i} successful")
            i += 1

    # Pytorch dataloader block (works if preprocessing block has not been run, or if NUM_WORKERS < 2,
    # or if s3fs version is <= 0.4.2, otherwise hangs indefinitely on the first batch)
    dataset = MultiCsvDataset(KEYS)
    loader = DataLoader(dataset, batch_size=10, num_workers=NUM_WORKERS)
    i = 1
    for batch in loader:
        print(f"Batch {i} successful")
        i += 1

authors: bradenkinard martindurant


text:
20181220 - meeting

@dpaez and I exchanged via mail about having a online meeting to share what we do about DAT. This is community building and as such we want to open it to other attendees.
First meeting:
Thu, 20 Dec 2018 at 15:00 GMT  - Online.
Not sure how we are meeting yet, but if you are interested please raise your hand here.

What about https://meet.jit.si/ ?

https://meet.jit.si/DATcomm-comm

Thanks for taking initiative on this!

authors: dkastl joehand martinheidegger

repo: dat-land/comm-comm


text:
Readded Integration tests

Based on #529 this PR readds the integration tests and fixes a few bugs.
Highlighting the changes:

It reintroduces command line options to specify where the data should be stored: https://github.com/dat-land/dat-desktop/commit/51c3b2476bcaf840f680574a3f43d92314b2eba0
It reintroduces the formerly missing dat document title: https://github.com/dat-land/dat-desktop/commit/3b5336f6dba969ece6e3e93bd5d06d2c6acde4ce
It reintroduces the former lib/monkeyPatch.js to make sure that the sharing of folders can be tested: https://github.com/dat-land/dat-desktop/commit/1fb670e7b6894246997b03e4dffafa4fc21f8cf6
It stops opening the developer tools (as this prevents the integration tests, and it shouldn't land in the deployment anyways): https://github.com/dat-land/dat-desktop/commit/ff25ba841bfc956ac8a49d72ee91d1a72aaef428#diff-168726dbe96b3ce427e7fedce31bb0bcL37
It introduces consistent css-classnames for buttons as it was hard to figure out in the tests what is happening: https://github.com/dat-land/dat-desktop/commit/6273b0382f456237bd6fc35a404d9ffd2c028880
Kept only integration tests in tests/index.js, the other tests are covered by unit tests now.

Let me merged this PR into add/download to, and continue the add/download branch

repo: dat-land/dat-desktop


text:
Permissions errors in repos

Michael Mahoney (not currently a user in this repo so I can't link him) ran into problems after he tried some renaming and moving of files in order to pull fresh copies (see #11). Now he's getting permissions errors and is unable to delete some files in his repository.
@SamLau95 any ideas?

@choldgraf I think this should be resolved. I'm guessing that him moving files around cause the git checkout to error out without chowning the directories properly. I need to add a catch for that.

Hmm.. doesn't look solved for me?
e.g. I just used @AndrejGitHub 's link, https://data8.berkeley.edu/hub/interact?repo=history-connector&path=07423-0001-Data.csv, which works great and imports his data file into Jupyter.
Now I cannot actually delete it from my Jupyter environment; I just get a permission denied error.

Ah, there is in fact a bug. Looking into it now.
ᐧ
On Wed, Jan 20, 2016 at 2:55 PM, Carl Boettiger notifications@github.com
wrote:

Hmm.. doesn't look solved for me?
e.g. I just used @AndrejGitHub https://github.com/AndrejGitHub 's link,
https://data8.berkeley.edu/hub/interact?repo=history-connector&path=07423-0001-Data.csv,
which works great and imports his data file into Jupyter.
Now I cannot actually delete it from my Jupyter environment; I just get a
permission denied error.
—
Reply to this email directly or view it on GitHub
https://github.com/data-8/connector-instructors/issues/12#issuecomment-173390612
.

--
Sam Lau
EECS | UC Berkeley | May 2017
(562) 565-4336 | samlau95@berkeley.edu
ᐧ

Note that when a the interact link clones a repo, the repo ends up being owned by root, not the by the user.  The contents of the repo show up as being owned by the user, but with read only permission, so we cannot delete these files.  Thanks for all the help!

Yup. The error is in https://github.com/data-8/DS8-Interact/blob/master/app/util.py#L9 since I change the ownership of the file to that of the parent directory (which belongs to root).

Let me know when this is pulled and I'll let Michael know to give it a shot again...

It's deployed on both ds8 and data8 I believe. Let me know if he's still
running into issues. I didn't test the sparse-checkout behavior thoroughly
on file moving and renaming so I make no guarantees about behavior at the
moment.
ᐧ
On Wed, Jan 20, 2016 at 6:09 PM, Chris Holdgraf notifications@github.com
wrote:

Let me know when this is pulled and I'll let Michael know to give it a
shot again...
—
Reply to this email directly or view it on GitHub
https://github.com/data-8/connector-instructors/issues/12#issuecomment-173428267
.

--
Sam Lau
EECS | UC Berkeley | May 2017
(562) 565-4336 | samlau95@berkeley.edu

hmm, just tested on data8 and when I use https://data8.berkeley.edu/hub/interact?repo=health-connector&path=Demo2.ipynb
I get health-connector repo added but still owned by root, and I cannot delete either health-connector directory or the Demo2.ipynb notebook.

Oops. Looking now.
ᐧ

Fixed. There were some issues in deploying and I forgot to get around to them.
This and #11 are now closed, so hopefully the interact links will be good to go for us.

authors: SamLau95 cboettig choldgraf


text:
[Feat] DEMO - this is how new widget task should look like

Purpose
The widget shows number of accidents per year, divided into categories (light / severe categories)
Wireframe (provided by product team - for each widget)
Design - use generic bar chart design (provided by product team)

API (widget date provided by backed team)
"name": "accident_count_by_accident_year",
  "data":  {
       "items": [
          {
            "label_key": "2017"
            "series": [
              { "label_key":  "light", "value": 55},
              { "label_key":  "severe", "value": 5},
              { "label_key":  "fatal", "value": 1},
            ]
          },
          {
            "label_key": "2018"
            "series": [
              { "label_key":  "light", "value": 50},
              { "label_key":  "severe", "value": 3},
              { "label_key":  "fatal", "value": 3},
            ]
          }
        ]
        },
        "text": {
          "title": "widget title bla bla"
          "labels_map": {
            "light": "\u05e7\u05d8\u05dc\u05e0\u05d9\u05ea"
            "severe": "\u05e7\u05e9\u05d4"
            "light": "\u05e7\u05dc\u05d4"
          }
        }
}

Additional context
Anything else you wish to add?

This task was completed with a different design

authors: MichalOren yuvalbl


text:
Fix/expression test

Summary

Changes to support date/time in expressions
Added actual test to test values in ExpressionTest
Added a directive parse-timestamp-as-date to convert unix timestamp in millis to ZonedDateTime.
Added corresponding test for parse-timestamp-as-date

https://builds.cask.co/browse/HYP-WT205-2

Latest build is green. Squashing and merging.

repo: data-integrations/wrangler


text:
Use builtin timestampadd and timestampdiff functions for dateadd/datediff macros if available.

Description
Uses builtin timestampadd and timestampdiff functions for dateadd/datediff macros if available.
The functions timestampadd and timestampdiff have been available since DBR 10.4. Those are equivalent to what dateadd/datediff macros are trying to achieve.

Thanks! merging.

repo: databricks/dbt-databricks


text:
Use F.datediff() for subtraction of dates as a workaround.

Since currently we don't support timedelta type in pandas, we haven't support subtraction of dates, but we already have a workaround for subtraction of timestamps returning long instead of timedelta. We can also support subtraction of dates returning int.
We should revisit after we support timedelta type.

Codecov Report

Merging #1439 into master will increase coverage by 0.07%.
The diff coverage is 100.00%.

@@            Coverage Diff             @@
##           master    #1439      +/-   ##
==========================================
+ Coverage   94.83%   94.91%   +0.07%
==========================================
  Files          34       34
  Lines        8078     8082       +4
==========================================
+ Hits         7661     7671      +10
+ Misses        417      411       -6

Impacted Files
Coverage Δ

databricks/koalas/base.py
98.06% <100.00%> (+0.42%)
:arrow_up:

databricks/koalas/frame.py
96.43% <0.00%> (+0.20%)
:arrow_up:

databricks/koalas/datetimes.py
99.11% <0.00%> (+0.88%)
:arrow_up:

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 9d97ffc...073156b. Read the comment docs.

authors: codecov-io ueshin

repo: databricks/koalas


text:
Add docs: Type Support In Koalas

Added documents "Type Support In Koalas" to describe which type is supported in Koalas and which type is not.

Codecov Report

Merging #1906 (46f69d9) into master (674cdd2) will decrease coverage by 2.70%.
The diff coverage is n/a.

@@            Coverage Diff             @@
##           master    #1906      +/-   ##
==========================================
- Coverage   94.14%   91.44%   -2.71%
==========================================
  Files          41       41
  Lines        9979     9915      -64
==========================================
- Hits         9395     9067     -328
- Misses        584      848     +264

Impacted Files
Coverage Δ

databricks/koalas/usage_logging/__init__.py
25.66% <0.00%> (-66.65%)
:arrow_down:

databricks/koalas/usage_logging/usage_logger.py
47.82% <0.00%> (-52.18%)
:arrow_down:

databricks/koalas/__init__.py
68.75% <0.00%> (-21.25%)
:arrow_down:

databricks/conftest.py
89.83% <0.00%> (-10.17%)
:arrow_down:

databricks/koalas/spark/functions.py
88.88% <0.00%> (-7.41%)
:arrow_down:

databricks/koalas/accessors.py
86.00% <0.00%> (-7.00%)
:arrow_down:

databricks/koalas/namespace.py
78.17% <0.00%> (-5.13%)
:arrow_down:

databricks/koalas/generic.py
88.88% <0.00%> (-4.79%)
:arrow_down:

databricks/koalas/frame.py
93.59% <0.00%> (-3.15%)
:arrow_down:

databricks/koalas/utils.py
93.18% <0.00%> (-2.89%)
:arrow_down:

... and 14 more

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 674cdd2...46f69d9. Read the comment docs.

authors: codecov-io itholic


text:
Support limit push down in to_html

This patch inlines to_html docs from pandas, and supports limit push down when max_rows is specified, so we don't need to pull in all the data.

LGTM. Let me cherry-pick workaround separately right way at https://github.com/databricks/koalas/pull/209

authors: HyukjinKwon rxin


text:
Fix Series.getitem to work properly

Resolves #933
>>> kser = ks.Series([10, 20, 15, 30, 45], ['A', 'A', 'B', 'C', 'D'])
>>> kser['A']
A    10
A    20
Name: 0, dtype: int64
>>>
>>> kser['B']
15

For MultiIndex
>>> midx = pd.MultiIndex([['lama', 'cow', 'falcon'],
...                       ['speed', 'weight', 'length']],
...                      [[0, 0, 0, 1, 1, 1, 2, 2, 2],
...                       [0, 1, 2, 0, 1, 2, 0, 1, 2]])
>>> kser = ks.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3], index=midx)
>>> pser = kser.to_pandas()

>>> kser['lama']
lama  speed      45.0
      weight    200.0
      length      1.2
Name: 0, dtype: float64

>>> pser['lama']
speed      45.0
weight    200.0
length      1.2
Name: 0, dtype: float64

while i'm here, i'm going to fix to cover below case.
>>> midx = pd.MultiIndex([['lama', 'cow', 'falcon'],
...                       ['speed', 'weight', 'length']],
...                      [[0, 0, 0, 1, 1, 1, 2, 2, 2],
...                       [0, 1, 2, 0, 1, 2, 0, 1, 2]])
>>> kser = ks.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3], index=midx)
>>> pser = kser.to_pandas()

>>> pser[('lama', 'speed')]
45.0

>>> kser[('lama', 'speed')]
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
...

Codecov Report

:exclamation: No coverage uploaded for pull request base (master@465861c). Click here to learn what that means.
The diff coverage is 100%.

@@           Coverage Diff           @@
##             master   #934   +/-   ##
=======================================
  Coverage          ?    92%
=======================================
  Files             ?     34
  Lines             ?   6388
  Branches          ?      0
=======================================
  Hits              ?   5877
  Misses            ?    511
  Partials          ?      0

Impacted Files
Coverage Δ

databricks/koalas/series.py
95.63% <100%> (ø)

Continue to review full report at Codecov.

Legend - Click here to learn more
Δ = absolute <relative> (impact), ø = not affected, ? = missing data
Powered by Codecov. Last update 465861c...2f1e6a8. Read the comment docs.

Seems like the examples for MultiIndex are different between Koalas and pandas?

@ueshin oops, i think i was just my mistake
they actually work same.
>>> midx = pd.MultiIndex([['lama', 'cow', 'falcon'],
...                       ['speed', 'weight', 'length']],
...                      [[0, 0, 0, 1, 1, 1, 2, 2, 2],
...                       [0, 1, 2, 0, 1, 2, 0, 1, 2]])
>>> kser = ks.Series([45, 200, 1.2, 30, 250, 1.5, 320, 1, 0.3], index=midx)
>>> pser = kser.to_pandas()

>>> kser['lama']
speed      45.0
weight    200.0
length      1.2
Name: 0, dtype: float64

>>> pser['lama']
speed      45.0
weight    200.0
length      1.2
Name: 0, dtype: float64

authors: codecov-io itholic ueshin


text:
[53] Update compatibility to Sklearn .18.

Currently, spark-sklearn gives deprecation warnings when used with sklearn version .18 because several classes in grid_search and cross_validation were refactored into a new module called model_selection. The changes here make spark-sklearn compatible with the changes introduced in sklearn .18.
The most critical changes reflected in the new version of sklearn is that:
sklearn.model_selection.GridSearchCV now has:
cv_results_ : dict of numpy (masked) ndarrays - A dict with keys as column headers and values as columns, that can be imported into a pandas DataFrame.
best_estimator_ : estimator - Estimator that was chosen by the search, i.e. estimator which gave highest score (or smallest loss if specified) on the left out data. Not available if refit=False.
best_score_ : float - Score of best_estimator on the left out data.
best_params_ : dict - Parameter setting that gave the best results on the hold out data.
best_index_ : int - The index (of the cv_results_ arrays) which corresponds to the best candidate parameter setting.
scorer_ : function - Scorer function used on the held out data to choose the best parameters for the model.
n_splits_ : int - The number of cross-validation splits (folds/iterations).
While spark-sklearn.GridSearchCV has:
grid_scores_ : list of named tuples
best_estimator_ : estimator - Estimator that was chosen by the search, i.e. estimator which gave highest score (or smallest loss if specified) on the left out data. Not available if refit=False.
best_score_ : float - Score of best_estimator on the left out data.
best_params_ : dict - Parameter setting that gave the best results on the hold out data.
scorer_ : function - Scorer function used on the held out data to choose the best parameters for the model.
The biggest is that sklearn added the more comprehensive cv_results_ which adds data that the formerly compatible grid_scores_ is lacking.
Note: This version of spark-sklearn is not compatible with sklearn <= .17.

Currently, spark-sklearn gives deprecation warnings when used with sklearn version .18 because several classes in grid_search and cross_validation were refactored into a new module called model_selection. The changes here make spark-sklearn compatible with the changes introduced in sklearn .18.
The most critical changes reflected in the new version of sklearn is that:
sklearn.model_selection.GridSearchCV now has:
cv_results_ : dict of numpy (masked) ndarrays - A dict with keys as column headers and values as columns, that can be imported into a pandas DataFrame.
best_estimator_ : estimator - Estimator that was chosen by the search, i.e. estimator which gave highest score (or smallest loss if specified) on the left out data. Not available if refit=False.
best_score_ : float - Score of best_estimator on the left out data.
best_params_ : dict - Parameter setting that gave the best results on the hold out data.
best_index_ : int - The index (of the cv_results_ arrays) which corresponds to the best candidate parameter setting.
scorer_ : function - Scorer function used on the held out data to choose the best parameters for the model.
n_splits_ : int - The number of cross-validation splits (folds/iterations).
While spark-sklearn.GridSearchCV has:
grid_scores_ : list of named tuples
best_estimator_ : estimator - Estimator that was chosen by the search, i.e. estimator which gave highest score (or smallest loss if specified) on the left out data. Not available if refit=False.
best_score_ : float - Score of best_estimator on the left out data.
best_params_ : dict - Parameter setting that gave the best results on the hold out data.
scorer_ : function - Scorer function used on the held out data to choose the best parameters for the model.
The biggest is that sklearn added the more comprehensive cv_results_ which adds data that the formerly compatible grid_scores_ is lacking.
Note: This version of spark-sklearn is not compatible with sklearn <= .17.

CC @dsackin

Oh!  I just realized: since we're switching from the deprecated GridSearch to the new model_selection.GridSearchCV, we'll have to switch to those tests as well.  test_grid_search_1.py and test_grid_search_2.py do a bit of Python magic to leverage the existing sklearn tests, but hopefully we can just switch to the new sklearn submodule and have it work.

repo: databricks/spark-sklearn


text:
Including a schemeURI with a nameIdentifier that is a URL will concat…

…enate the schemeURI and the nameIdentifier
Fixes #136
Purpose

When a nameIdentifier property contains both a schemeURI attribute and a nameIdentifier in the form of a URL, bolognese concatenates the schemeURI and nameIdentifier, resulting in incorrectly normalized nameIdentifiers like https://ror.org/https://ror.org/04p8xrf95 . This does not affect ORCIDs, which have specific normalization logic applied.
closes: #136
Approach

Rather than simply concatenating schemeURIs and nameIdentifiers when a schemeURI is present, the code now adopts the logic from the affiliationIdentifier code:
https://github.com/datacite/bolognese/blob/5a01ebd48784fa837db351405a8153e1bbb5c18d/lib/bolognese/author_utils.rb#L147
This only concatenates the schemeURI if "https://" is not present in the nameIdentifier and a schemeURI is present. It also performs some additional URL normalization found here:
https://github.com/datacite/bolognese/blob/5a01ebd48784fa837db351405a8153e1bbb5c18d/lib/bolognese/utils.rb#L610
Open Questions and Pre-Merge TODOs

Unfortunately, applying this logic to, for example, ISNIs can be problematic. As it currently exists, the implementation fails a test where nameIdentifier 0000 0003 5752 6882 with schemeURI http://isni.org/isni/ is normalized to http://isni.org/isni/0000%200003%205752%206882 (with the spaces escaped) when the test expects http://isni.org/isni/0000 0003 5752 6882. I would argue that neither the original test nor the fix produce correct results, since the ISNI is correct in the original expression 0000 0003 5752 6882.
The available options seem to be:

Keep the current fix but apply it only to RORs and add ROR-specific logics, e.g. always assume the schemeURI is https://ror.org/ when the nameIdentifierScheme is ROR.  For other identifier schemes, simply transcribe the schemeURI and nameIdentifier as entered.
Create additional logics for other identifiers like ISNIs.
Make no attempt at normalization and leave nameIdentifiers and schemeURIs as entered if they are not ORCIDs.

Types of changes

[x] Bug fix (non-breaking change which fixes an issue)

[ ] New feature (non-breaking change which adds functionality)

[ ] Breaking change (fix or feature that would cause existing functionality to change)

Reviewer, please remember our guidelines:

Be humble in the language and feedback you give, ask don't tell.
Consider using positive language as opposed to neutral when offering feedback. This is to avoid the negative bias that can occur with neutral language appearing negative.
Offer suggestions on how to improve code e.g. simplification or expanding clarity.
Ensure you give reasons for the changes you are proposing.

we just found out that

Having looked at this again, maybe go with option 1:
Keep the current fix but apply it only to RORs and add ROR-specific logics, e.g. always assume the schemeURI is https://ror.org/ when the nameIdentifierScheme is ROR. For other identifier schemes, simply transcribe the schemeURI and nameIdentifier as entered.
i.e. lets just handle ROR as the main issue here for now and not try and be clever elsewhere.

authors: codycooperross kjgarza richardhallett

repo: datacite/bolognese


text:
Fix git_repo.py bug

Running the tests from a freshly cloned repo result in an error in TestGit at line 24:
repo = repo_loader.get_repo("https://github.com/sbenthall/bigbang.git", in_type = "remote")
The error is cause by:
time_index = pd.DatetimeIndex(raw["Time"], periods = 24)
The error message is:
TypeError: __new__() got an unexpected keyword argument 'periods'
My setup in short is the following:
platform linux -- Python 3.9.1, pytest-6.2.1, py-1.10.0, pluggy-0.13.1
pandas-1.2.1
I fixed it by changing the line 122f in git_repo.py to:
time_index = pd.DatetimeIndex(raw["Time"]).to_period("H")
time_index = utils.add_freq(time_index, freq=None)

Note: as my editor automatically removes unnecessary white spaces, more lines were changed besides the two that are crucial.

Thanks for this. Merging

authors: Christovis sbenthall

repo: datactive/bigbang


text:
Correction for raw affiliation Eco-Procédés Optimisation et Aide à la Décision - UR UPJV 4669; SFR Condorcet

Correction needed for raw affiliation Eco-Procédés Optimisation et Aide à la Décision - UR UPJV 4669; SFR Condorcet
raw_affiliation_name: Eco-Procédés Optimisation et Aide à la Décision - UR UPJV 4669; SFR Condorcet
new_rors: 01gyxrk03
previous_rors:
works_examples: W4230443616;W2971070078;W4289021411;W4226146294
contact: 9712e8e8353c4d74024d6baa6acaf2e6:0d37520a12d483c075ebb90a4314a3b4 @ u-picardie.fr

This issue was accepted and ingested by the OpenAlex team on 2024-10-10. The new affiliations should be visible within the next 7 days.

repo: dataesr/openalex-affiliations


text:
Correction for raw affiliation Aix-Marseille Université - Faculté des Arts, Lettres, Langues et Sciences Humaines; Centre Camille Jullian - Histoire et archéologie de la Méditerranée et de l'Afrique du Nord de la protohistoire à la fin de l'Antiquité; Histoire et Sources des Mondes antiques; Université Jean Moulin - Lyon 3

Correction needed for raw affiliation Aix-Marseille Université - Faculté des Arts, Lettres, Langues et Sciences Humaines; Centre Camille Jullian - Histoire et archéologie de la Méditerranée et de l'Afrique du Nord de la protohistoire à la fin de l'Antiquité; Histoire et Sources des Mondes antiques; Université Jean Moulin - Lyon 3
raw_affiliation_name: Aix-Marseille Université - Faculté des Arts, Lettres, Langues et Sciences Humaines; Centre Camille Jullian - Histoire et archéologie de la Méditerranée et de l'Afrique du Nord de la protohistoire à la fin de l'Antiquité; Histoire et Sources des Mondes antiques; Université Jean Moulin - Lyon 3
new_rors: 050sat078;05b5c0584;035xkbk20;01yx7av22
previous_rors: 04yavcg77;050sat078;05b5c0584;035xkbk20
works_examples: W4388715814
contact: e0cb0911c4398e3165eec5010537575a:977c983fd379a005e2c61504933e @ ens-lyon.fr

This issue was accepted and ingested by the OpenAlex team on 2024-11-01. The new affiliations should be visible within the next 7 days.


text:
Installation solaire à domicile (🌡 et 🚗)

Bonjour!
Je charge ma voiture à l’énergie solaire, et chauffe aussi ma maison en partie par le solaire. J’ai pu passer à côté mais il ne me semble pas que ça fasse partie des propositions. (Bon après les factures de bois d’électricité et de gaz sont très faibles par rapport à la superficie de la maison, donc peut-être que c’est pris en compte par ce biais?)

Nous n'avons pas encore d'estimation de l'empreinte d'une installation solaire à domicile.
A creuser :)

S'il s'agit d'électricité venant d'un fournisseur d'électricité "verte" --> cf. F.A.Q
S'il s'agit bien d'une installation solaire à domicile, nous n'avons en effet pas encore d'estimation car c'est un cas encore minoritaire. En première approximation vous pouvez renseigner 0 dans votre consommation élec mais c'est bien entendu sous estimer l'impact réel qui se devra de prendre l'impact lié à la construction et à l'installation des panneaux PV

Je ferme au profit de  #624

authors: Benjamin-Boisserie-ABC laem publicodes

repo: datagir/nosgestesclimat


text:
fix(docs-site) remove free trial notes

Checklist

[ ] The PR conforms to DataHub's Contributing Guideline (particularly Commit Message Format)
[ ] Links to related issues (if applicable)
[ ] Tests for the changes have been added/updated (if applicable)
[ ] Docs related to the changes have been added/updated (if applicable). If a new feature has been added a Usage Guide has been added for the same.
[ ] For any breaking change/potential downtime/deprecation/big changes an entry has been made in Updating DataHub

@maggiehays i already bumped it up in the solutions page PR, but ill copy it here so it gets out quicker

@jayacryl got signoff from Lydia - good to ship

authors: jayacryl maggiehays

repo: datahub-project/datahub


text:
feat(ingest/s3): type aware directory sorting

Adding comparator to dir sorting which can sort dirs as numbers if it is number
Checklist

[ ] The PR conforms to DataHub's Contributing Guideline (particularly Commit Message Format)
[ ] Links to related issues (if applicable)
[ ] Tests for the changes have been added/updated (if applicable)
[ ] Docs related to the changes have been added/updated (if applicable). If a new feature has been added a Usage Guide has been added for the same.
[ ] For any breaking change/potential downtime/deprecation/big changes an entry has been made in Updating DataHub

Main question is around how to best handle folders with multiple equals signs

Hive partitioning is usually like :
mydir/2022/12/11
or like this:
mydir/year=2022/month=12/day=11
I think these are the most common ones and for the others it should be fine to compare as string


text:
Backend/simple matching

First commit

@JaneBellaiche can you link the PR to the corresponding clubhouse story? Thanks!

[ch61527]

[ch-61527]

Unit tests are failing 👿

Oupsidoups ! That's because I've modified Tagger arguments after committing the test file
But now it's all good !

Top! Merge & ca part en WE!

authors: JaneBellaiche alexcombessie

repo: dataiku/dss-plugin-nlp-analysis


text:
Refactor docs

Changes done:

Updated the results format
Removed the logo as it was not visible after the deployment

Can one of the admins verify this patch?

ok to test

repo: datakaveri/iudx-data-ingestion-server


text:
Setting up environments

Closes #42.

note: for some reason celery jobs aren't kicking in for me ATM (well -- with yesterday's version, started with ./up) and don't see anything in docker log for those instances on that... yet to figure out how to troubleshoot and/or compare to behavior in master, where I believe it worked

@yarikoptic Try again with the latest code.  Using that, the celery containers come up fine for me.

authors: jwodder yarikoptic

repo: datalad/datalad-registry


text:
How to find all documents from collection

In ruby mongo driver to find all documents in collection is
collection.find

However, in this driver expect to have some arguments pass to it. Which argument should I pass to find method in order to get the ideal result ?

@dylandy here is how I did it: https://github.com/sam0x17/crystal-mongo-orm/blob/3262bc6880d7c6ec8e2f756bfc9a1a8050b71bc2/src/mongo_orm/querying.cr#L88
Note that my ORM is able to do this out of the box using the Model.all method, as you mention.
https://github.com/sam0x17/crystal-mongo-orm

You can get all documents of a collection (as BSON objects) like this:
docs = [] of BSON
collection.find(BSON.new).each do |doc|
  docs << doc
end

I don't know if it's the best way, but it works fine.

authors: Pyroglyph dylandy sam0x17


text:
🛑 Teddit is down

In c9cd956, Teddit (https://teddit.mha.fi) was down:

HTTP code: 502
Response time: 482 ms

Resolved: Teddit is back up in 86be685.


text:
[Question] Is Datashim still not ready for production?

Hi
I see a comment from 2019 on datashim/src/csi-s3/README.md that says:
CSI for S3
This is a Container Storage Interface (CSI) for S3 (or S3 compatible) storage. This can dynamically allocate buckets and mount them via a fuse mount into any container.
Status
This is still very experimental and should not be used in any production environment. Unexpected data loss could occur depending on what mounter and S3 storage backend is being used.
Is this still true?
I saw a that the release was this year, do you guys still experience data loss?
Thanks

Closing this issue. Please reopen or start a discussion, if further investigation is needed.

repo: datashim-io/datashim


text:
Cluster Init/Connect : Memory leak test

Attempt to automate some memory profiling tests

Rebased after merging #297.

I think having this test automated is awesome. I've added a few nits, but overall looks good.
The test covers the situation described by the user.
In the future, we could add a one against a real cluster but I think maybe a more suitable place would be the endurance test: just recording memory growth somewhere, wdyt?

There is a remaining issue related to the JetBrains.DotMemoryUnit dependency, that is causing TravisCI to fail.
You need to add the reference in the Cassandra.IntegrationTests.csproj file as well, in the path ..\packages\JetBrains.DotMemoryUnit.2.3.20160517.113140\Lib\dotMemory.Unit.dll
I know its a nightmare to add new references in the project thanks to the dual toolchain, but it should be straightforward once we migrate to VS2017 (see CSHARP-548).

Fails on TravisCI under mono 5 but not on Jenkins... 😡

I'm not able to reproduce on OSX under Mono 5...

Job Creator build failures are intermittent, we need to create an test item regarding this behavior.

ok, I've created CSHARP-571 with some of the failures we've encountering.

authors: jorgebay landim

repo: datastax/csharp-driver


text:
JAVA-845: Backport JAVA-843 to 2.1

Backported from 3.0 branch.

looks great, :+1:

repo: datastax/java-driver


text:
Some issues when using playground

Failed to launch playground. because I have a stoped docker container with the name "mysql" which conflict with playground container name, rename to "playground-mysql" "playground-postgresql"?   And I noticed playground export some famous ports like 3306 , maybe conflict with the port in local host.
I don't know when the playground is ready to use,  maybe we could provide a more meaningful message when it's ready or add some documents.
Add document about when playground is ready, which metalake, schema, tables are pre-created.
Add document about how to explore existing metalake, schema, tables.

I also had an issue with ports as I had Postgres running locally, and the playground Postgres docker uses the same port. It's not entirely unexpected, but it could cause some people issues.

I also had an issue with ports as I had Postgres running locally, and the playground Postgres docker uses the same port. It's not entirely unexpected, but it could cause some people issues.

Maybe we can add the ports to the readme document and tell users how modify the ports.

repo: datastrato/gravitino-playground


text:
Add tests for config backward compatibility

After #617 our preferred config format will change, so we will need to make sure that we don't break old repos. We have a few tests for that already, but that is not enough.

Already added compat tests to tests/test_data_cloud.py

repo: dataversioncontrol/dvc


text:
feature request: Ignore words

I wish suggest a filter based on words that will let the script ignore post/messages that contain it.

added to list
https://github.com/users/datawhores/projects/2

authors: CannotTouch datawhores

repo: datawhores/ofscraper


text:
add basic menu to header

for #271
The menu is still unstyled and the button to open the menu isn't clickable yet (css issue I think).
Once we have all the links in there we need, I'll make them open the target in a browser, as expected.

@juliangruber What's missing here? Tested visually, LGTM!

authors: Kriesse juliangruber

repo: datproject/dat-desktop


text:
General TCP+TLS Documentation?

Can this library support TCP + TLS communications? is it under "other"?
Would be nice to see some clarification in this! thanks!

Sorry to take so long to respond.   I recently started using the https://github.com/joeferner/node-http-mitm-proxy package to support https, and manage the certificates.  The Middleman proxy listens on port 9999 (default) for incoming HTTP Connect requests (https tunnel), and https requests.  Your browser proxy can be configured to proxy https to localhost:9999.  Backend microservices can also be configured to send https messages to localhost:9999.
The https: tab configures URL paths to route https messages received from a microservice to the origin server.  The proxy: tab by default captures all https traffic from the browser.
I hope that helps.

authors: davechri ghost

repo: davechri/middleman-proxy


text:
NullPointException Attempt to read from field "Anim.listener" on a null object reference

Please provide as much of the following information as possible. Please do not raise issues to ask for help developing your app.
Expected behaviour
won't crash
Actual behaviour
sometimes crash
Steps to reproduce
zoom and move image frequently, there is a chance that crash.
may be add and remove animation continuously cause to error.
Fatal Exception: java.lang.NullPointerException
Attempt to read from field 'com.davemorrissey.labs.subscaleview.SubsamplingScaleImageView$OnAnimationEventListener com.davemorrissey.labs.subscaleview.SubsamplingScaleImageView$Anim.listener' on a null object reference
com.davemorrissey.labs.subscaleview.SubsamplingScaleImageView$Anim.access$2800 (SubsamplingScaleImageView.java:1898)
com.davemorrissey.labs.subscaleview.SubsamplingScaleImageView.onDraw (SubsamplingScaleImageView.java:1018)
android.view.View.draw (View.java:23017)
android.view.View.updateDisplayListIfDirty (View.java:21885)
android.view.ViewGroup.recreateChildDisplayList (ViewGroup.java:4526)
android.view.ViewGroup.dispatchGetDisplayList (ViewGroup.java:4499)
android.view.View.updateDisplayListIfDirty (View.java:21838)
android.view.ViewGroup.recreateChildDisplayList (ViewGroup.java:4526)
android.view.ViewGroup.dispatchGetDisplayList (ViewGroup.java:4499)
android.view.View.updateDisplayListIfDirty (View.java:21838)
android.view.ViewGroup.recreateChildDisplayList (ViewGroup.java:4526)
android.view.ViewGroup.dispatchGetDisplayList (ViewGroup.java:4499)
android.view.View.updateDisplayListIfDirty (View.java:21838)
android.view.ViewGroup.recreateChildDisplayList (ViewGroup.java:4526)
android.view.ViewGroup.dispatchGetDisplayList (ViewGroup.java:4499)
android.view.View.updateDisplayListIfDirty (View.java:21838)

(Include your setup code, and where relevant, your layout XML)
Affected devices
Many Android devices
(Specific devices, screen densities, SDK versions)
Affected images
(Attach images you have problems with)

@davemorrissey I also have the same issue, please provider same information.

authors: HeAiTong PeacefulGemini


text:
Update specs2-core, specs2-scalacheck to 4.13.2

Updates

org.specs2:specs2-core
org.specs2:specs2-scalacheck

from 4.12.12 to 4.13.2.
I'll automatically update this PR to resolve conflicts as long as you don't change it yourself.
If you'd like to skip this version, you can just close this PR. If you have any feedback, just mention me in the comments below.
Configure Scala Steward for your repository with a .scala-steward.conf file.
Have a fantastic day writing Scala!

Ignore future updates
Add this to your .scala-steward.conf file to ignore future updates of this dependency:
updates.ignore = [ { groupId = "org.specs2" } ]

labels: test-library-update, early-semver-minor, semver-spec-minor, commit-count:1

Superseded by #241.

repo: davenverse/epimetheus-circuit


text:
feat: upgrade to Cats Effect 3

Depends on #277.

[x] Get compiling
[x] Review joining strategy for AutoFetchingCache with @ChristopherDavenport .
[x] Get tests green; looked for help here.

Any update on this?

I forgot this was still held up on my stuff not working. Not sure when I'm going to get back to it.

Did not mean to close.

@ChristopherDavenport let me know if you want me to submit a WIP PR for as far as I got trying to get these testing working with virtual time on CE3. I did make some progress on it, but never got past them failing.
Anything else you'd like to see in order to get this merged? Sorry that I forgot about it for so long.

authors: Ali-Mahmood Kazark

repo: davenverse/mules


text:
Added Swifty Lion blog

Added Swifty Lion blog

Thanks1

repo: daveverwer/iOSDevDirectory


text:
Import the rollbar library regardless of whether it's enabled in the config

This resolves #71 and #76.

Hi @davewasmer , is there anything in particular blocking this PR?

We have a legit use case for this: We want to be able to configure the { payload: { person: {...} } attribute in staging/production but otherwise don't want to report errors to Rollbar during development. Being able to load Rollbar this way suits the scenario nicely.
Without this enhancement, the alternative is either not reporting the person attribute or having chatting Rollbar signals in development... both are less than ideal.

@bradcrawford my main hesitation is that at the moment I don't actually have an Ember app using this addon in production, so I'm now a bit removed from the use cases / needs here, and it puts this lower on my priority list.
My other hesitation is I seem to remember having problems always including Rollbar in the past, but I can't seem to dig up the specific issue. I might be misremembering too - it certainly seems to make sense to include it all the time if it's available via static import.
I'll merge this in and release a beta tag on npm so you all can give it a shot. If that looks good, I'll release a stable version with it as well.

0.3.1-beta.1 is out, please give it a try and let me know if you hit any snags

Thanks @davewasmer , trying it out now

@davewasmer - Changes work a treat, thank you very much!

authors: bradcrawford davewasmer shunchu svvitale

repo: davewasmer/ember-cli-rollbar


text:
Add YouTube timestamp functionality

Add a new page/route to make it easier to get timestamps for videos for proper indexing.

Our use case is that we have people who have a transcript in an excel sheet and want to align speech to ~100ms so we can display it. See: https://corpus.gaelg.im/docs/YouTube-L-Quirk-Coraaghyn-Vannin
They need to know the StartTime and EndTime for a sentence.
Realistically any method can work (and we CAN go for better tech), but an easy workaround is to give them a YouTube Player which shows the current time, so they can drop in a reasonable 'start' and 'end'
I would do this as a separate page (route in React terminology), as it's 'content creator' functionality, rather than something that a user of the corpus would need

Basic functionality: display current time
Optional extras: allow a user to input a start [+ end] and play the video between those two points

authors: david-allison lauterb

repo: david-allison/manx-corpus-search


text:
Still getting no route errors on production server

I am trying to get rid of routing errors on my production server..and tried your gem, but I still get this routing error...
ActionController::RoutingError (No route matches [GET] "/apple-touch-icon-152x152.png"):

I added quiet_safari to my gemfile.  Is there anything else I need to do?
Thanks for writing a gem that will hopefully get rid of the frustrating apple touch icon errors!

Submitted PR #2 which fixes this issue.


text:
Error item expanable viewHolder

I used animation for sub items when I clicked on the parent items.
But when I collase the parent item then the next parent item doesn't receive the onClick event anymore!
If you don't use the animation for the sub item, then everything works properly.
Can you give me a solution to fix this problem?
Thank all

@ngocjx Were you able to resolve this issue?

authors: arsonistAnt ngocjx

repo: davideas/FlexibleAdapter


text:
Cannot access index in properties of dynamic object

When trying to access vlues of an array (or dictionary) inside a dynamic object, I get the error:
DynamicExpresso.Exceptions.ParseException : No applicable indexer exists in type 'Object' (at index 7).
    [Test]
    public void Get_value_of_a_nested_array()
   {
       dynamic dyn = new ExpandoObject();
       dyn.Sub = new int[] {42};
       var interpreter = new Interpreter().SetVariable("dyn", (object)dyn);
       Assert.AreEqual(dyn.Sub[0], interpreter.Eval("dyn.Sub[0]"));
}

This is also mentioned on Stack Overflow, https://stackoverflow.com/questions/53040955/how-can-i-use-dynamic-variables-with-anonymous-types

Thanks @NielsUll Not sure when I can work on it, so any help is appreciated.

Closed by #142

authors: NielsUll davideicardi

repo: davideicardi/DynamicExpresso


text:
La Skill solicitada no responde

Hola
He intentanbdo probar este codigo en alexa pero la consola me tira el siguiente error:
La Skill solicitada no responde

Hola Edinsof,
Acabo de probar y me funciona perfectamente, intenta revisar que este emparejado el Endpoint con Lambda y en Lambda que desencadenador este puesto la Skill id.
Saludos,

¿Podría explicar en detalle cómo instalar con imágenes impresas que no entendí?

authors: davidespier edinsof saniellocutor

repo: davidespier/alexa-skill-busca-tu-ritmo


text:
Two extensions in webstore ?

There are apparently two versions of the extension in the webstore - https://chrome.google.com/webstore/search/foxish

Correct, not ideal but at one point the extension was removed by Google so
I re-added it while the issue was resolved. Now there are users on both and
I don't want to strand them by removing one of the listings.
Its the exact same offering on both listings.
On Mon, Aug 27, 2018 at 7:13 PM Ԝеѕ notifications@github.com wrote:

There are apparently two versions of the extension in the webstore -
https://chrome.google.com/webstore/search/foxish
—
You are receiving this because you are subscribed to this thread.
Reply to this email directly, view it on GitHub
https://github.com/davidhampgonsalves/foxish/issues/7, or mute the
thread
https://github.com/notifications/unsubscribe-auth/AAK6zQiykvzOEa73OKZWMDuKT1CSpaDjks5uVG8GgaJpZM4WOlnH
.

authors: davidhampgonsalves wesinator

repo: davidhampgonsalves/foxish


text:
running pip install --user ddcci-plasmoid-backend give an error that I can't get arround

EDIT: Nevermind
I ran pip install ddcci-plasmoid-backend --break-system-packages and it worked. Could you please add that in the readme file for arch users, or whomever you think would get this message?
I used to be able to install it just fine, but now the system is not liking pip and it throws this error when I run pip install ddcci-plasmoid-backend
This environment is externally managed
╰─> To install Python packages system-wide, try 'pacman -S
   python-xyz', where xyz is the package you are trying to
   install.

   If you wish to install a non-Arch-packaged Python package,
   create a virtual environment using 'python -m venv path/to/venv'.
   Then use path/to/venv/bin/python and path/to/venv/bin/pip.

   If you wish to install a non-Arch packaged Python application,
   it may be easiest to use 'pipx install xyz', which will manage a
   virtual environment for you. Make sure you have python-pipx
   installed via pacman.

note: If you believe this is a mistake, please contact your Python installation or OS distribution provider. You can override this, at the risk of breaking your Python installation or OS, by passing --break-system-packages.
hint: See PEP 668 for the detailed specification.

I Have installed pip and tried - still failed
I have used pipx (it was suggested when I searched) - still failed
Not sure what else I can do to install the  ddcci-plasmoid-backend . It is not available anywhere to install

With pipx it complains that the package doesn't exist.

Just to make sure does pipx not find the package or does the widget not find the backend? If the latter is true,

You can always install a local package use pipx install /path/to/this/repo/backend

Maybe we should document pipx stuff, because recent distro no longer allow global or user pip installation

You can always install a local package use pipx install /path/to/this/repo/backend

The issue is that ddcci-plasmoid-backend isn't available to download anywhere when I searched it. Unless it's available under a different name then I don't know.

Just to make sure does pipx not find the package or does the widget not find the backend? If the latter is true, then you need to set the backend executable command to ~/.local/bin/ddcci_plasmoid_backend.

Both. Widget can't find it because it is not installed and here is what I get when running pipx
 pipx install --user ddcci-plasmoid-backend
usage: pipx [-h] [--version]
            {install,uninject,inject,upgrade,upgrade-all,uninstall,uninstall-all,reinstall,reinstall-all,list,run,runpip,ensurepath,environment,completions}
            ...
pipx: error: unrecognized arguments: --user

You can always install a local package use pipx install /path/to/this/repo/backend

The issue is that ddcci-plasmoid-backend isn't available to download anywhere when I searched it. Unless it's available under a different name then I don't know.

I mean:
git clone https://github.com/davidhi7/ddcci-plasmoid
pipx install ./ddcci-plasmoid/backend/

Just to make sure does pipx not find the package or does the widget not find the backend? If the latter is true, then you need to set the backend executable command to ~/.local/bin/ddcci_plasmoid_backend.

Both. Widget can't find it because it is not installed and here is what I get when running pipx
 pipx install --user ddcci-plasmoid-backend
usage: pipx [-h] [--version]
            {install,uninject,inject,upgrade,upgrade-all,uninstall,uninstall-all,reinstall,reinstall-all,list,run,runpip,ensurepath,environment,completions}
            ...
pipx: error: unrecognized arguments: --user

It's  pipx install ddcci-plasmoid-backend
https://pypa.github.io/pipx/docs/

You can always install a local package use pipx install /path/to/this/repo/backend

The issue is that ddcci-plasmoid-backend isn't available to download anywhere when I searched it. Unless it's available under a different name then I don't know.

I mean:
git clone https://github.com/davidhi7/ddcci-plasmoid
pipx install ./ddcci-plasmoid/backend/

Oh wow. 😂
That's crazy how I missed that.

Just to make sure does pipx not find the package or does the widget not find the backend? If the latter is true, then you need to set the backend executable command to ~/.local/bin/ddcci_plasmoid_backend.

Both. Widget can't find it because it is not installed and here is what I get when running pipx
 pipx install --user ddcci-plasmoid-backend
usage: pipx [-h] [--version]
            {install,uninject,inject,upgrade,upgrade-all,uninstall,uninstall-all,reinstall,reinstall-all,list,run,runpip,ensurepath,environment,completions}
            ...
pipx: error: unrecognized arguments: --user

The right command is pipx install ddcci-plasmoid-backend without --user, pipx always install packages into user's home.
https://pypa.github.io/pipx/docs/

I used almost the same command, but I kept adding python to it.
I think this whole pipx thing should be added to the readme. So, noobs like me don't get stranded.

I used almost the same command, but I kept adding python to it. I think this whole pipx thing should be added to the readme. So, noobs like me don't get stranded.

I created a PR about this issue: #42 , any ideas are welcome :smile_cat:

authors: CatEricka KarkanAlzwayed davidhi7


text:
4.3.5 release breaks package import when used with @types/iframe-resizer package

Describe the bug
The 4.3.5 release changed the library's exports.
This release requires a change to the import: import {iframeResize} from 'iframe-resizer';
Prior to this release, we imported the library like this: import {iframeResizer} from 'iframe-resizer';
We also use typescript, and the @types/iframe-resizer package, which exports the iframeResizer function.
The discrepancy in exports (iframeResize vs iframeResizer) makes it seem like this 4.3.5 release should have been labeled as major, rather than minor.
Was this change intended? If so, we can adjust types separately.

Bugger, not it wasn't.

OK, not sure how that happened, but it now once again supports both. Technically iframeResize() is correct and what all the docs refer to, but I guess changing it in typings outside a major version is a bad idea. For now could you allow both?

Thank you very much for making this change!

repo: davidjbradshaw/iframe-resizer


text:
Ignored iFrame, already setup.

Hello,
The page has 2 buttons, first button create iframe, print own iframe, delete iframe, after this operation i get warnings(see bottom of message)
and iframe resizer stops working. when i click second buttton, modal window is opening, but iframe resizer does not resizing iframe inside modal window.
when i don't printing page, iframe resizer works well.
I think it could happening because  print button create and delete own iframe. How can i fix this?
(2)iframeResizer.min.js:8 [iFrameSizer][Host page: iFrameResizer0] Ignored iFrame, already setup.
iframeResizer.min.js:8 [iFrameSizer][Host page: fb_xdm_frame_http] Ignored iFrame, already setup.
iframeResizer.min.js:8 [iFrameSizer][Host page: fb_xdm_frame_https] Ignored iFrame, already setup

https://github.com/davidjbradshaw/iframe-resizer#close-1

Hello david,
Are we supposed to "close" the iframe?

If you are adding and removing iFrames from the page then it is best to close them. If you are reusing the same IDs then you must close them.

So basically, my iframeResize() call is just: iframeResize(). I don't have any parameters in my iframeResize call from the main page.
Would the iframe page still be ok to call the close function? If not, could you point me in the right direction on where I am going wrong?

The issue is about the ID tag on the iFrame element, if you remove an
iFrame and then reuse the ID on another iFrame you create a conflict.
Either don’t place an ID on the iFrame, or use unique ones.
If you have to reuse then follow the link above.
On Wed, Nov 23, 2016 at 9:52 AM, ikOrbis notifications@github.com wrote:

So basically, my iframeResize() call is just: iframeResize(). I don't
have any parameters in my iframeResize call from the main page.
Would the iframe page still be ok to call the close function? If not,
could you point me in the right direction on where I am going wrong?
—
You are receiving this because you modified the open/close state.
Reply to this email directly, view it on GitHub
https://github.com/davidjbradshaw/iframe-resizer/issues/327#issuecomment-262471518,
or mute the thread
https://github.com/notifications/unsubscribe-auth/AAkHEhMFfu6AqYVNij2saLXyqCksybZcks5rBAzbgaJpZM4HlTJJ
.

--
David J. Bradshaw )'( dave@bradshaw.net

Hey Guys,
But we can use class instead of ID.
I had the same issue and fixed it by replacing ID with Class.
Thanks.


text:
Update README.md

Add note about multiple iframes on one page. Then they all need a unique id.

Hi thanks, you seem to have made this change to an old version of the docs. The troubleshooting section now has it's own separate file. Can you please make the update there.
https://github.com/davidjbradshaw/iframe-resizer/blob/master/docs/troubleshooting.md

There is already a note on multiple frames on the updated troubleshotting file, closed this pull.

authors: davidjbradshaw markvantilburg


text:
Is it possible to define default (catch all) transition for a particular state?

Bug or feature request?
Question or feature request.
Description:
In switch...caseor pattern-matching syntax:
switch (value) {
  case 1:
    //
  case 2:
    //
  default:
    // ....
}

There is a way to catch all of other unmatched values using default or _. Is there any approach to do this in xstate?
(Feature) Potential implementation:
Required! If you would like to see a feature or enhancement make its way to xstate, please describe:

What the API would look like

Use _  to catch all of non SOMETHING event:
{
  states: {
    a: {
      on: {
        SOMETHING: 'b',
        _: 'c'
      }
    },
    b: {
      on: {}
    },
    c: {
      on: {}
    },
  }
}

or '*':
{
  states: {
    a: {
      on: {
        SOMETHING: 'b',
        '*': 'c'   // <- add quotes to avoid SyntaxError
      }
    },
    b: {
      on: {}
    },
    c: {
      on: {}
    },
  }
}

If this is a breaking change

Probably No. If we do not name any events to _ or *.

If this is part of the existing SCXML specification

Probably yes? As * event:
<state id=s">
   <transition event="e" cond="x==1" target="s1"/>
   <transition event="e" target="s2"/>
   <transition event="*" target="s3"/>
</state>

I think (to follow with the SCXML spec) we should both support:

* for any event without an explicit transition on the state node (explicitly defined events would take precedence)
foo.* (foo.bar.*, etc.) for matching namespaced events

What about partial wildcards support in XState? As I see, in PR #578 was added only global wildcard support. Is there any plans for this?

@elyzov do you refer to the event descriptors ending with .* (like `foo.*)?

@Andarist Exactly! I think it's very useful ability to redirect bunch of events through one route.

What about partial wildcards support in XState? As I see, in PR #578 was added only global wildcard support. Is there any plans for this?

I think this should be supported, and it's now possible with TypeScript 🎉
Want to create a new issue so we can track this?  It is an SCXML feature.

Want to create a new issue so we can track this? It is an SCXML feature.

I've created the idea #1716

authors: Andarist chentsulin davidkpiano elyzov

repo: davidkpiano/xstate